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Updated: Feb 2, 2026

Quantitative Comparison of cis-Regulatory Element CRE Activities in Transgenic Drosophila melanogaster
Published on: December 19, 2011
Quantitative analysis of multi-element synergy stabilizing performance: comparison of three methods with respect to
Sandra M S F Freitas1,2,3, Paulo B de Freitas2,3,4, Mechelle M Lewis3,5
1Graduate Program in Physical Therapy, City University of São Paulo, São Paulo, SP, Brazil.
Abstract:
A number of analyses associated with the uncontrolled manifold (UCM) hypothesis have been used recently to investigate stability of actions across populations. We explored whether some of those methods have an advantage for clinical studies because they require fewer trials to achieve consistent findings. We compared the number of trials needed for the analysis of inter-trial variance, analysis of motor equivalence, and analysis in the space of referent coordinates. Young healthy adults performed four-finger accurate force production tasks under visual feedback with the right (dominant) and left hand over three days. Three methods [analytical (M1), experimental (M2), and cumulative mean (M3) methods] were used to define the minimal number of trials required to reach certain statistical criteria. Two of these methods, M1 and M2, showed qualitatively similar results. Fewer trials (M1: 5-13, M2: 4-10) were needed for analysis of motor equivalence compared to inter-trial variance analysis (M1: 14-24, M2: 10-14). The third method (M3) showed no major differences among the outcome variables. The index of synergy in the inter-trial variance analysis required a very small number of trials (M1, M2: 2-4). Variables related to referent coordinates required only a few trials (under 3), whereas the synergy index in this analysis required the largest number of trials (M1: 24-34, M2: 12-16). This is the first study to quantify the number of trials needed for UCM-based methods of assessing motor coordination broadly used in clinical studies. Clinical studies can take advantage of specific recommendations based on the current data regarding the number of trials needed for each analysis thus allowing minimizing the test session duration without compromising data reliability.
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